Nonparametric inference for the proportionality function in the random censorship model

By generalizing the proportional hazards model, we introduce a new function β( t ), which we call the proportionality function, and which we show plays a role in studying aspects of the randomly censored model. We develop an asymptotically efficient nonparametric estimator of β( t ), establish its u...

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Published in:Journal of nonparametric statistics Vol. 15; no. 2; pp. 151 - 169
Main Authors: Hollander, Myles, Laird, Glen, Song, Kai-Sheng
Format: Journal Article
Language:English
Published: Taylor & Francis Group 01-04-2003
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Abstract By generalizing the proportional hazards model, we introduce a new function β( t ), which we call the proportionality function, and which we show plays a role in studying aspects of the randomly censored model. We develop an asymptotically efficient nonparametric estimator of β( t ), establish its uniform consistency, and obtain a weak convergence result. Furthermore, a confidence band for β( t ), based on the bootstrap, is developed. The results are applied to an actual dataset.
AbstractList By generalizing the proportional hazards model, we introduce a new function β( t ), which we call the proportionality function, and which we show plays a role in studying aspects of the randomly censored model. We develop an asymptotically efficient nonparametric estimator of β( t ), establish its uniform consistency, and obtain a weak convergence result. Furthermore, a confidence band for β( t ), based on the bootstrap, is developed. The results are applied to an actual dataset.
Author Song, Kai-Sheng
Laird, Glen
Hollander, Myles
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10.1109/TR.1981.5221168
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Snippet By generalizing the proportional hazards model, we introduce a new function β( t ), which we call the proportionality function, and which we show plays a role...
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StartPage 151
SubjectTerms Nonparametric Estimation
Proportional Hazards Model
Proportionality Function
Random Censorship Model
Uniform Convergence
Weak Convergence
Title Nonparametric inference for the proportionality function in the random censorship model
URI https://www.tandfonline.com/doi/abs/10.1080/1048525031000089329
Volume 15
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